The volume, variety, and velocity properties of big data and the valuable information it
contains have motivated the investigation of many new parallel data processing systems in …

The continuous increase in computational capacity over the past years has produced an
overwhelming flow of data or big data, which exceeds the capabilities of conventional …

The majority of large-scale data intensive applications executed by data centers are based
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …

Cloud computing has been emerging as a flexible and powerful computational architecture
to offer ubiquitous services to users. It accommodates interconnected hardware and …

Complex query types, huge data volumes, and very high read/update ratios make the
indexing techniques designed and tuned for traditional database systems unsuitable for …

With the incoming 5G access networks, it is forecasted that Fog computing (FC) and Internet
of Things (IoT) will converge onto the Fog-of-IoT paradigm. Since the FC paradigm spreads …

As the demands for big data analytics keep growing rapidly in scientific applications and
online services, MapReduce and its open-source implementation Hadoop gained popularity …

With increasingly inexpensive storage and growing processing power, the cloud has rapidly
become the environment of choice to store and analyze data for a variety of applications …

The authors investigate the impact of big data's velocity on greening IP over WDM networks.
They classify the processing velocity of big data into two modes: expedited‐data and relaxed …

The energy efficiency of cloud computing has recently attracted a great deal of attention. As
a result of raised expectations, cloud providers such as Amazon and Microsoft have started …